With the development of technology, parallel computing applications have been
commonly executed in large data centers. These parallel computing applications
include the computation phase and communication phase, and work is completed by
repeatedly executing these two phases. However, due to the ever-increasing
computing demands, large data centers are burdened with massive communication
demands. Coflow is a recently proposed networking abstraction to capture
communication patterns in data-parallel computing frameworks. This paper
focuses on the coflow scheduling problem in identical parallel networks, where
the goal is to minimize makespan, the maximum completion time of coflows. The
coflow scheduling problem in huge data center is considered one of the most
significant NP-hard problems. In this paper, coflow can be considered as
either a divisible or an indivisible case. Distinct flows in a divisible coflow
can be transferred through different network cores, while those in an
indivisible coflow can only be transferred through the same network core. In
the divisible coflow scheduling problem, this paper proposes a
(3βm2β)-approximation algorithm, and a
(38ββ3m2β)-approximation algorithm, where m is the number
of network cores. In the indivisible coflow scheduling problem, this paper
proposes a (2m)-approximation algorithm. Finally, we simulate our proposed
algorithm and Weaver's [Huang \textit{et al.}, In 2020 IEEE International
Parallel and Distributed Processing Symposium (IPDPS), pages 1071-1081, 2020.]
and compare the performance of our algorithms with that of Weaver's